The documents listed below are incorporated herein by reference.    [1] Eichel, P., Ives, R. W., “Compression of Complex-Valued SAR Images” IEEE Transactions on Image Processing, Vol. 8. NO. October 1999    [2] Eichel, P. H., LCDR Ives, R. W., “Very low rate compression of speckled SAR imagery”, Sandia Report, SAND97-2383/1, Internal Distribution Only, October 1997.    [3] Wang, Z., Bovik, A. C., Sheikh, H. R., Simoncelli E. P. “Image Quality Assessment: From Error Visibility to Structural Similarity, IEEE Transactions on Image Processing, Vol. 13, NO. 4, April 2004    [4] Ives, R. W., Eichel, P., Magotra, N., “A New SAR Image Compression Quality Metric”, IEEE Trans., pp. 1143-1146, May 1999    [5] Salomon, D., “Data Compression: The Complete Reference”, Fourth Edition. Springer, 2007, ISBN 9781846286026    [6] Jao, J. K., “SAR Image Processing for Moving Target Focusing”, Proc. 2001 IEEE Radar Conf., pp. 58-63    [7] Cumming, I. G., Wong, F. H., “Digital Processing of Synthetic Aperture Radar Data: Algorithms and Implementation”, Artech House 2005, ISBN: 9781580530583    [8] Jakowatz, C. V., Wahl, D. E., Eichel, P. H., Ghiglia, D. C., Thompson, P. A., “Spotlight-Mode Synthetic Aperture Radar: A signal Processing Approach”, Kluwer Academic Publishers, 4th printing, 1999, ISBN 0-7923-9677-4    [9] Rohwer, J. A., “Open-Loop Adaptive Filtering for Speckle Reduction in Synthetic Aperture Radar Images”, Sandia Report, Sand2000-1421, Unlimited Release, June 2000    [10.] Doerry, A. W., “Anatomy of a SAR Impulse Response”, Sandia Report SAND2007-5042, Unlimited Release, August 2007    [11] Lim, J. S., “Two-Dimensional Signal and Image Processing”, Prentice Hall PTR, 1990, ISBN 0-13-935322-4    [12] Reddy, B. S., Chatterji, B. N., “An FFT-Based Technique for Translation, Rotation, and Scale-Invariant Image Registration”, IEEE Transactions on Image Processing, Vol. 5, NO. 8, pp. 1266-1271, August 1996    [13] Unser, M., Thevenaz, P., Yaroslaysky, L., “Convolution-Based Interpolation for Fast, High-Quality Rotation of Images”, IEEE Transactions on Image Processing, Vol. 4, NO. 10, pp. 1371-1381, October 1995.    [14] Turkowski, K., “Filters for Common Resampling Tasks”, www.worldserver.com/turk/computergraphics/ResamplingFilters.pdf, Apr. 10, 1990    [15] Acton, S. T., Yu, Y. “Speckle Reducing Anisotoropic Diffusion”, IEEE Transactions on Image Processing, Vol. 11, NO. 11, pp. 1260-1270, November 2002
U.S. Pat. No. 7,498,968 (incorporated by reference herein) describes a synthetic aperture radar (SAR) system that is capable of forming high-resolution SAR images at near video rates, e.g., many times a second. The rate of image update allows users to determine when moving targets start moving, when and where they stop, the direction of motion, and how fast they are moving. Further, the radar shadows of moving targets can be used to determine the position and identity of the targets (including even slow moving targets), and display the target motion from frame to frame. SAR systems and techniques such as described in U.S. Pat. No. 7,498,968 are also referred to herein generally as “VideoSAR”.
In airborne SAR systems, the digitized radar return (echo response) from the target scene is often referred to as a phase history. VideoSAR collects a continuous stream of phase histories without a defined aperture center. With no specified aperture center, the stream of phase histories can be processed into any arbitrary aperture. Full-size synthetic apertures with mutually overlapping phase histories, are used to form respectively corresponding images. The overlapping apertures enable the near video frame rate, and each aperture provides the basis for an independent, fine-resolution SAR image. The greater the aperture overlap, the higher the SAR image rate. The images can be displayed and analyzed in sequence, yielding a ‘movie-like’ appearance of the scene.
The video product produced by VideoSAR is typically either a clip or a stream that contains a relatively large amount of data. A VideoSAR clip product is a file containing a closed set of SAR images, for example, thousands of SAR images captured over a few minutes. A VideoSAR stream product may be a true real-time video constructed as a sequence of SAR images whose length is not known a priori. The number of bytes needed for a typical 2000×2000 pixel high-resolution SAR image is on the order of 3.5 megabytes for an 8-bit SAR intensity image. As an example, assuming a frame rate of 3 frames/second, the bit rate required for transmission of the data would be approximately 84 megabits/second (84 Mbps).
Communication links conventionally available for real time transmission of the data are typically bit rate-limited, and may have an effective bit rate as low as, for example, 1.5 Mbps. Data compression may be implemented to accommodate the bit rate limitations of the transmission link, but the aforementioned high data rates associated with VideoSAR products dictate correspondingly high compression ratios. Consider, for instance, the example of the aforementioned 84 Mbps VideoSAR product transmitted on the aforementioned 1.5 Mbps link. This requires a 56:1 compression ratio, without even accounting for typical communication overhead such as protocol headers, metadata, and data link intermittency. The amount of compression applied may also be quantified in terms of bits/pixel (bpp). For instance, in the aforementioned 35 megabyte VideoSAR sequence example, each pixel represents the scene intensity as an unsigned 8-bit integer (UINT8), and there are thus 8 bits/pixel (8 bpp). The aforementioned 56:1 compression ratio would correspond to compression of the bpp parameter from 8 bpp to about 0.143 bpp. (Note that, all other things being equal, the bpp parameter relates directly to the bit rate of the communication link—multiplying the bit rate of the link by a factor of n results in multiplication of the permitted bpp rate by the same factor n.) By any measure, however, high compression ratios such as mentioned above will of course degrade quality at final display. For example, critical image details are eliminated and unwanted artifacts are introduced.
Commercial-off-the-shelf (COTS) video codecs are appealing due to the transportability of the resulting products, the availability of compatible display client software, and the availability of other features such as multiple product streaming, vector overlays, extensible metadata and multicast delivery schemes. However, the most appealing COTS codecs are typically designed for optimal performance with cinematic and broadcast television content, and consequently are not particularly effective at providing the aforementioned large compression ratios required by VideoSAR.
There are known compression algorithms that provide effective spatial, i.e., intra-frame compression of individual SAR image frames. Compression of VideoSAR products has also been investigated. Examples of various known approaches are described in documents [1], [2] and [3] above. The known approaches typically utilize custom designed codecs that are tailored to the algorithms. Moreover, the known approaches do not addresses temporal compression, i.e., frame-to-frame (inter-frame) compression techniques which, as recognized by the present work, would be useful in conjunction with the aforementioned movie-like nature of VideoSAR products.
Referring again to the aforementioned example of a nominal minimum compression ratio of 56:1, and assuming that each frame of a VideoSAR sequence can be spatially compressed by a factor of 30:1 while maintaining sufficient image quality, the corresponding bpp value would be 0.2667. Temporal compression could help achieve the desired value of 0.143 bpp, but that requires an additional compression ratio of about 1.9:1. (The 30:1 spatial compression ratio and the 1.9:1 temporal compression ratio would multiply to provide the desired 56:1 ratio.) Available COTS codecs are capable of providing spatial and temporal compression.
It is desirable in view of the foregoing to provide for the use of COTS codecs with spatial and temporal compression capabilities to compress highly data intensive image streams, such as VideoSAR products, sufficiently to achieve adequate image quality at the receiver over relatively low capacity communication links.